This is simply and empirically wrong, but you're free to believe it if you find simple falsehoods more comfortable than nuanced truths.
> I’m tired of people’s political views unleashing this group of people in my neighborhood.
People need to stop using "political" when they mean "contrary to my prejudices about the world".
> I would appreciate another approach.
Likewise.
In your own words, the truth might be more nuanced than the current falsehood-du-jour.
Exhibit A: https://news.ycombinator.com/item?id=37738543#37756115a
> Indicators of "concentrated disadvantage" (e.g., racial heterogeneity, poverty, and family disruption) are among the strongest and most stable predictors.
Absolutely nothing in the article being discussed in this comment aligns with the comment I was replying to:
> It’s no mystery that “guns and drugs on the table” crime is perpetrated by low-IQ psychopaths
Moreover, I both saw and discussed this article, so it's absolutely not the case that I'm ignoring inconvenient truths. The truths under discussion are both extremely convenient to my point, and directly addressed by me.
I don't know if I said anywhere that poverty is the only contributing factor, or is fully required for crime to occur (clearly white collar crime is a counterexample), but I do strongly believe that it is a leading factor for many varieties of crime, particularly the "guns and drugs on the table" types of crimes that the police love to prosecute. Thanks for your condescending evaluation of my motivations and your correction of my language summarizing a study. I disagree that "very strong" isn't a useful descriptor of quantitative findings, but I suppose everyone is free to have their own preferences. Sorry for your frustration, but I do think that it's misguided.
> The strongest effects found in this meta-analysis were from "strength of non-economic institutions" and "unemployment (length considered)".
Unsure how strong your understanding of multivariate regression is, but I would imagine that including two big covariates of poverty in an analysis would reduce the effect size of the actual poverty variable. "Family disruption" seems like another big correlate of poverty. The link you provided doesn't work for me so can't investigate any of these deeper, but I imagine that drawing out a little causal diagram of all these possible causes might help you reconcile the study you found with the one I provided. Have a good one!